Entity relation extraction method

An entity relationship and relationship technology, applied in the field of information processing, can solve problems such as high labor costs and inability to deal with Internet volume entities and relationship information.
CN108733792AActive Publication Date: 2018-11-02PEKING UNIV SHENZHEN GRADUATE SCHOOL
8 Cites 80 Cited by

Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
PEKING UNIV SHENZHEN GRADUATE SCHOOL
Publication Date
2018-11-02

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses an entity relation extraction method. The method comprises the following steps: inputting pre-processed information into a word sequence neural network and an entity sequence neural network, respectively performing relation extraction, thereby two networks to mutually learn through a bidirectional knowledge distillation way, and integrating a relation prediction result of two networks as the final prediction result to output. Since the pre-processed information is input into two different neural networks, two neutral networks are trained at the same time and mutually used as the teacher of the opposite party to perform the adjusting of the neural network parameter; the weighted integrated output are performed on the extraction relations output by two neural networks, two neural networks are used for removing noise data in the training sample in a cooperative way, the respective advantages of two different neural networks are integrated to realize the aims of optimizing and reducing noise.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of information processing, in particular to an entity relationship extraction method. Background technique

[0002] Information Extraction refers to the process of extracting information such as entities, events, and relationships from a piece of text, forming structured data and storing it in a database for user query and use. Relation Extraction is the key content of information extraction, which aims to discover the semantic relationship between entities in the real world. In recent years, this technology has been widely used in many machine learning and natural language processing tasks, including the construction and completion of Knowledge Graph (KG), information retrieval, question answering system, etc.

[0003] Traditional relation extraction research generally adopts supervised machine learning methods, which regard relation extraction as a classification problem, use manually labeled training data, and tra...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More